Overview

Brought to you by YData

Dataset statistics

 Prior Order Profile ReportTrain Order Profile Report
Number of variables1010
Number of observations324344891384617
Missing cells20780680
Missing cells (%)0.6%0.0%
Duplicate rows00
Duplicate rows (%)0.0%0.0%
Total size in memory2.4 GiB105.6 MiB
Average record size in memory80.0 B80.0 B

Variable types

 Prior Order Profile ReportTrain Order Profile Report
Numeric88
Categorical22

Alerts

Prior Order Profile ReportTrain Order Profile Report
eval_set has constant value "prior" eval_set has constant value "train" Constant
days_since_prior_order has 2078068 (6.4%) missing values Alert not present in this datasetMissing
order_dow has 6209666 (19.1%) zeros order_dow has 324026 (23.4%) zeros Zeros
days_since_prior_order has 448698 (1.4%) zeros days_since_prior_order has 17044 (1.2%) zeros Zeros

Reproduction

 Prior Order Profile ReportTrain Order Profile Report
Analysis started2024-11-01 20:57:22.5732592024-11-01 21:07:35.426262
Analysis finished2024-11-01 21:07:29.6684372024-11-01 21:08:03.001191
Duration10 minutes and 7.1 seconds27.57 seconds
Software versionydata-profiling v0.0.dev0ydata-profiling v0.0.dev0
Download configurationconfig.jsonconfig.json

Variables

order_id
Real number (ℝ)

 Prior Order Profile ReportTrain Order Profile Report
Distinct3214874131209
Distinct (%)9.9%9.5%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean1710748.51706297.6
 Prior Order Profile ReportTrain Order Profile Report
Minimum21
Maximum34210833421070
Zeros00
Zeros (%)0.0%0.0%
Negative00
Negative (%)0.0%0.0%
Memory size247.5 MiB10.6 MiB
2024-11-01T17:08:07.401083image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

 Prior Order Profile ReportTrain Order Profile Report
Minimum21
5-th percentile170925170761
Q1855943843370
median17110481701880
Q325655142568023
95-th percentile32502093249514.2
Maximum34210833421070
Range34210813421069
Interquartile range (IQR)17095711724653

Descriptive statistics

 Prior Order Profile ReportTrain Order Profile Report
Standard deviation987300.7989732.65
Coefficient of variation (CV)0.577116210.5800469
Kurtosis-1.1991283-1.2066256
Mean1710748.51706297.6
Median Absolute Deviation (MAD)854783861914
Skewness-0.000489741460.0063315648
Sum5.5487254 × 10132.3625687 × 1012
Variance9.7476267 × 10119.7957072 × 1011
MonotonicityIncreasingIncreasing
2024-11-01T17:08:07.584426image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1564244 145
 
< 0.1%
790903 137
 
< 0.1%
61355 127
 
< 0.1%
2970392 121
 
< 0.1%
2069920 116
 
< 0.1%
3308010 115
 
< 0.1%
2753324 114
 
< 0.1%
2499774 112
 
< 0.1%
2621625 109
 
< 0.1%
77151 109
 
< 0.1%
Other values (3214864) 32433284
> 99.9%
ValueCountFrequency (%)
1395075 80
 
< 0.1%
2813632 80
 
< 0.1%
949182 77
 
< 0.1%
2869702 76
 
< 0.1%
341238 76
 
< 0.1%
312611 75
 
< 0.1%
1465173 74
 
< 0.1%
1355077 74
 
< 0.1%
653280 72
 
< 0.1%
288915 72
 
< 0.1%
Other values (131199) 1383861
99.9%
ValueCountFrequency (%)
2 9
 
< 0.1%
3 8
 
< 0.1%
4 13
< 0.1%
5 26
< 0.1%
6 3
 
< 0.1%
7 2
 
< 0.1%
8 1
 
< 0.1%
9 15
< 0.1%
10 15
< 0.1%
11 5
 
< 0.1%
ValueCountFrequency (%)
1 8
 
< 0.1%
36 8
 
< 0.1%
38 9
 
< 0.1%
96 7
 
< 0.1%
98 49
< 0.1%
112 11
 
< 0.1%
170 17
 
< 0.1%
218 5
 
< 0.1%
226 13
 
< 0.1%
349 11
 
< 0.1%
ValueCountFrequency (%)
1 8
 
< 0.1%
36 8
 
< 0.1%
38 9
 
< 0.1%
96 7
 
< 0.1%
98 49
< 0.1%
112 11
 
< 0.1%
170 17
 
< 0.1%
218 5
 
< 0.1%
226 13
 
< 0.1%
349 11
 
< 0.1%
ValueCountFrequency (%)
2 9
 
< 0.1%
3 8
 
< 0.1%
4 13
< 0.1%
5 26
< 0.1%
6 3
 
< 0.1%
7 2
 
< 0.1%
8 1
 
< 0.1%
9 15
< 0.1%
10 15
< 0.1%
11 5
 
< 0.1%

product_id
Real number (ℝ)

 Prior Order Profile ReportTrain Order Profile Report
Distinct4967739123
Distinct (%)0.2%2.8%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean25576.33825556.236
 Prior Order Profile ReportTrain Order Profile Report
Minimum11
Maximum4968849688
Zeros00
Zeros (%)0.0%0.0%
Negative00
Negative (%)0.0%0.0%
Memory size247.5 MiB10.6 MiB
2024-11-01T17:08:07.786745image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

 Prior Order Profile ReportTrain Order Profile Report
Minimum11
5-th percentile33763397
Q11353013380
median2525625298
Q33793537940
95-th percentile4755947601
Maximum4968849688
Range4968749687
Interquartile range (IQR)2440524560

Descriptive statistics

 Prior Order Profile ReportTrain Order Profile Report
Standard deviation14096.68914121.272
Coefficient of variation (CV)0.551161360.55255682
Kurtosis-1.1408165-1.1537944
Mean25576.33825556.236
Median Absolute Deviation (MAD)1208012122
Skewness-0.021130583-0.022354791
Sum8.2955544 × 10113.5385598 × 1010
Variance1.9871664 × 1081.9941034 × 108
MonotonicityNot monotonicNot monotonic
2024-11-01T17:08:07.960320image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
24852 472565
 
1.5%
13176 379450
 
1.2%
21137 264683
 
0.8%
21903 241921
 
0.7%
47209 213584
 
0.7%
47766 176815
 
0.5%
47626 152657
 
0.5%
16797 142951
 
0.4%
26209 140627
 
0.4%
27845 137905
 
0.4%
Other values (49667) 30111331
92.8%
ValueCountFrequency (%)
24852 18726
 
1.4%
13176 15480
 
1.1%
21137 10894
 
0.8%
21903 9784
 
0.7%
47626 8135
 
0.6%
47766 7409
 
0.5%
47209 7293
 
0.5%
16797 6494
 
0.5%
26209 6033
 
0.4%
27966 5546
 
0.4%
Other values (39113) 1288823
93.1%
ValueCountFrequency (%)
1 1852
< 0.1%
2 90
 
< 0.1%
3 277
 
< 0.1%
4 329
 
< 0.1%
5 15
 
< 0.1%
6 8
 
< 0.1%
7 30
 
< 0.1%
8 165
 
< 0.1%
9 156
 
< 0.1%
10 2572
< 0.1%
ValueCountFrequency (%)
1 76
< 0.1%
2 4
 
< 0.1%
3 6
 
< 0.1%
4 22
 
< 0.1%
5 1
 
< 0.1%
7 1
 
< 0.1%
8 13
 
< 0.1%
9 5
 
< 0.1%
10 119
< 0.1%
11 2
 
< 0.1%
ValueCountFrequency (%)
1 76
< 0.1%
2 4
 
< 0.1%
3 6
 
< 0.1%
4 22
 
< 0.1%
5 1
 
< 0.1%
7 1
 
< 0.1%
8 13
 
< 0.1%
9 5
 
< 0.1%
10 119
< 0.1%
11 2
 
< 0.1%
ValueCountFrequency (%)
1 1852
0.1%
2 90
 
< 0.1%
3 277
 
< 0.1%
4 329
 
< 0.1%
5 15
 
< 0.1%
6 8
 
< 0.1%
7 30
 
< 0.1%
8 165
 
< 0.1%
9 156
 
< 0.1%
10 2572
0.2%

add_to_cart_order
Real number (ℝ)

 Prior Order Profile ReportTrain Order Profile Report
Distinct14580
Distinct (%)< 0.1%< 0.1%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean8.35107558.7580443
 Prior Order Profile ReportTrain Order Profile Report
Minimum11
Maximum14580
Zeros00
Zeros (%)0.0%0.0%
Negative00
Negative (%)0.0%0.0%
Memory size247.5 MiB10.6 MiB
2024-11-01T17:08:08.120657image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

 Prior Order Profile ReportTrain Order Profile Report
Minimum11
5-th percentile11
Q133
median67
Q31112
95-th percentile2223
Maximum14580
Range14479
Interquartile range (IQR)89

Descriptive statistics

 Prior Order Profile ReportTrain Order Profile Report
Standard deviation7.12667127.4239365
Coefficient of variation (CV)0.853383630.84767058
Kurtosis5.6438734.1722265
Mean8.35107558.7580443
Median Absolute Deviation (MAD)44
Skewness1.81807121.6855488
Sum2.7086287 × 10812126537
Variance50.78944255.114833
MonotonicityNot monotonicNot monotonic
2024-11-01T17:08:08.442482image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 3214874
 
9.9%
2 3058126
 
9.4%
3 2871133
 
8.9%
4 2664106
 
8.2%
5 2442025
 
7.5%
6 2213695
 
6.8%
7 1986020
 
6.1%
8 1766014
 
5.4%
9 1562640
 
4.8%
10 1378293
 
4.2%
Other values (135) 9277563
28.6%
ValueCountFrequency (%)
1 131209
 
9.5%
2 124364
 
9.0%
3 116996
 
8.4%
4 108963
 
7.9%
5 100745
 
7.3%
6 91850
 
6.6%
7 83142
 
6.0%
8 74601
 
5.4%
9 66618
 
4.8%
10 59401
 
4.3%
Other values (70) 426728
30.8%
ValueCountFrequency (%)
1 3214874
9.9%
2 3058126
9.4%
3 2871133
8.9%
4 2664106
8.2%
5 2442025
7.5%
6 2213695
6.8%
7 1986020
6.1%
8 1766014
5.4%
9 1562640
4.8%
10 1378293
4.2%
ValueCountFrequency (%)
1 131209
9.5%
2 124364
9.0%
3 116996
8.4%
4 108963
7.9%
5 100745
7.3%
6 91850
6.6%
7 83142
6.0%
8 74601
5.4%
9 66618
4.8%
10 59401
4.3%
ValueCountFrequency (%)
1 131209
0.4%
2 124364
0.4%
3 116996
0.4%
4 108963
0.3%
5 100745
0.3%
6 91850
0.3%
7 83142
0.3%
8 74601
0.2%
9 66618
0.2%
10 59401
0.2%
ValueCountFrequency (%)
1 3214874
232.2%
2 3058126
220.9%
3 2871133
207.4%
4 2664106
192.4%
5 2442025
176.4%
6 2213695
159.9%
7 1986020
143.4%
8 1766014
127.5%
9 1562640
112.9%
10 1378293
99.5%

reordered
Categorical

 Prior Order Profile ReportTrain Order Profile Report
Distinct22
Distinct (%)< 0.1%< 0.1%
Missing00
Missing (%)0.0%0.0%
Memory size247.5 MiB10.6 MiB
1
19126536 
0
13307953 
1
828824 
0
555793 

Length

 Prior Order Profile ReportTrain Order Profile Report
Max length11
Median length11
Mean length11
Min length11

Characters and Unicode

 Prior Order Profile ReportTrain Order Profile Report
Total characters324344891384617
Distinct characters22
Distinct categories11 ?
Distinct scripts11 ?
Distinct blocks11 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

 Prior Order Profile ReportTrain Order Profile Report
Unique00 ?
Unique (%)0.0%0.0%

Sample

 Prior Order Profile ReportTrain Order Profile Report
1st row11
2nd row11
3rd row00
4th row10
5th row01

Common Values

ValueCountFrequency (%)
1 19126536
59.0%
0 13307953
41.0%
ValueCountFrequency (%)
1 828824
59.9%
0 555793
40.1%

Length

2024-11-01T17:08:08.568122image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

Prior Order Profile Report

2024-11-01T17:08:08.663535image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Train Order Profile Report

2024-11-01T17:08:08.742579image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
ValueCountFrequency (%)
1 19126536
59.0%
0 13307953
41.0%
ValueCountFrequency (%)
1 828824
59.9%
0 555793
40.1%

Most occurring characters

ValueCountFrequency (%)
1 19126536
59.0%
0 13307953
41.0%
ValueCountFrequency (%)
1 828824
59.9%
0 555793
40.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 32434489
100.0%
ValueCountFrequency (%)
(unknown) 1384617
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1 19126536
59.0%
0 13307953
41.0%
ValueCountFrequency (%)
1 828824
59.9%
0 555793
40.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 32434489
100.0%
ValueCountFrequency (%)
(unknown) 1384617
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1 19126536
59.0%
0 13307953
41.0%
ValueCountFrequency (%)
1 828824
59.9%
0 555793
40.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 32434489
100.0%
ValueCountFrequency (%)
(unknown) 1384617
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1 19126536
59.0%
0 13307953
41.0%
ValueCountFrequency (%)
1 828824
59.9%
0 555793
40.1%

user_id
Real number (ℝ)

 Prior Order Profile ReportTrain Order Profile Report
Distinct206209131209
Distinct (%)0.6%9.5%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean102937.24103112.78
 Prior Order Profile ReportTrain Order Profile Report
Minimum11
Maximum206209206209
Zeros00
Zeros (%)0.0%0.0%
Negative00
Negative (%)0.0%0.0%
Memory size247.5 MiB10.6 MiB
2024-11-01T17:08:08.884742image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

 Prior Order Profile ReportTrain Order Profile Report
Minimum11
5-th percentile1046910425
Q15142151732
median102611102933
Q3154391154959
95-th percentile195736195696
Maximum206209206209
Range206208206208
Interquartile range (IQR)102970103227

Descriptive statistics

 Prior Order Profile ReportTrain Order Profile Report
Standard deviation59466.47859487.148
Coefficient of variation (CV)0.577696450.57691342
Kurtosis-1.2009235-1.2007212
Mean102937.24103112.78
Median Absolute Deviation (MAD)5149351608
Skewness0.0066119537-0.0003274701
Sum3.3387168 × 10121.4277171 × 1011
Variance3.536262 × 1093.5387208 × 109
MonotonicityNot monotonicNot monotonic
2024-11-01T17:08:09.047592image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
201268 3725
 
< 0.1%
129928 3638
 
< 0.1%
164055 3061
 
< 0.1%
186704 2936
 
< 0.1%
176478 2921
 
< 0.1%
182401 2907
 
< 0.1%
137629 2901
 
< 0.1%
33731 2888
 
< 0.1%
108187 2760
 
< 0.1%
4694 2735
 
< 0.1%
Other values (206199) 32404017
99.9%
ValueCountFrequency (%)
197541 80
 
< 0.1%
149753 80
 
< 0.1%
63458 77
 
< 0.1%
83993 76
 
< 0.1%
189951 76
 
< 0.1%
169647 75
 
< 0.1%
31611 74
 
< 0.1%
104741 74
 
< 0.1%
181991 72
 
< 0.1%
59321 72
 
< 0.1%
Other values (131199) 1383861
99.9%
ValueCountFrequency (%)
1 59
 
< 0.1%
2 195
< 0.1%
3 88
< 0.1%
4 18
 
< 0.1%
5 37
 
< 0.1%
6 14
 
< 0.1%
7 206
< 0.1%
8 49
 
< 0.1%
9 76
 
< 0.1%
10 143
< 0.1%
ValueCountFrequency (%)
1 11
 
< 0.1%
2 31
< 0.1%
5 9
 
< 0.1%
7 9
 
< 0.1%
8 18
< 0.1%
9 22
< 0.1%
10 4
 
< 0.1%
13 5
 
< 0.1%
14 11
 
< 0.1%
17 6
 
< 0.1%
ValueCountFrequency (%)
1 11
 
< 0.1%
2 31
< 0.1%
5 9
 
< 0.1%
7 9
 
< 0.1%
8 18
< 0.1%
9 22
< 0.1%
10 4
 
< 0.1%
13 5
 
< 0.1%
14 11
 
< 0.1%
17 6
 
< 0.1%
ValueCountFrequency (%)
1 59
 
< 0.1%
2 195
< 0.1%
3 88
< 0.1%
4 18
 
< 0.1%
5 37
 
< 0.1%
6 14
 
< 0.1%
7 206
< 0.1%
8 49
 
< 0.1%
9 76
 
< 0.1%
10 143
< 0.1%

eval_set
Categorical

 Prior Order Profile ReportTrain Order Profile Report
Distinct11
Distinct (%)< 0.1%< 0.1%
Missing00
Missing (%)0.0%0.0%
Memory size247.5 MiB10.6 MiB
prior
32434489 
train
1384617 

Length

 Prior Order Profile ReportTrain Order Profile Report
Max length55
Median length55
Mean length55
Min length55

Characters and Unicode

 Prior Order Profile ReportTrain Order Profile Report
Total characters1621724456923085
Distinct characters45
Distinct categories11 ?
Distinct scripts11 ?
Distinct blocks11 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

 Prior Order Profile ReportTrain Order Profile Report
Unique00 ?
Unique (%)0.0%0.0%

Sample

 Prior Order Profile ReportTrain Order Profile Report
1st rowpriortrain
2nd rowpriortrain
3rd rowpriortrain
4th rowpriortrain
5th rowpriortrain

Common Values

ValueCountFrequency (%)
prior 32434489
100.0%
ValueCountFrequency (%)
train 1384617
100.0%

Length

2024-11-01T17:08:09.179151image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

Prior Order Profile Report

2024-11-01T17:08:09.258567image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Train Order Profile Report

2024-11-01T17:08:09.337370image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
ValueCountFrequency (%)
prior 32434489
100.0%
ValueCountFrequency (%)
train 1384617
100.0%

Most occurring characters

ValueCountFrequency (%)
r 64868978
40.0%
p 32434489
20.0%
i 32434489
20.0%
o 32434489
20.0%
ValueCountFrequency (%)
t 1384617
20.0%
r 1384617
20.0%
a 1384617
20.0%
i 1384617
20.0%
n 1384617
20.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 162172445
100.0%
ValueCountFrequency (%)
(unknown) 6923085
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
r 64868978
40.0%
p 32434489
20.0%
i 32434489
20.0%
o 32434489
20.0%
ValueCountFrequency (%)
t 1384617
20.0%
r 1384617
20.0%
a 1384617
20.0%
i 1384617
20.0%
n 1384617
20.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 162172445
100.0%
ValueCountFrequency (%)
(unknown) 6923085
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
r 64868978
40.0%
p 32434489
20.0%
i 32434489
20.0%
o 32434489
20.0%
ValueCountFrequency (%)
t 1384617
20.0%
r 1384617
20.0%
a 1384617
20.0%
i 1384617
20.0%
n 1384617
20.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 162172445
100.0%
ValueCountFrequency (%)
(unknown) 6923085
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
r 64868978
40.0%
p 32434489
20.0%
i 32434489
20.0%
o 32434489
20.0%
ValueCountFrequency (%)
t 1384617
20.0%
r 1384617
20.0%
a 1384617
20.0%
i 1384617
20.0%
n 1384617
20.0%

order_number
Real number (ℝ)

 Prior Order Profile ReportTrain Order Profile Report
Distinct9997
Distinct (%)< 0.1%< 0.1%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean17.1420517.09141
 Prior Order Profile ReportTrain Order Profile Report
Minimum14
Maximum99100
Zeros00
Zeros (%)0.0%0.0%
Negative00
Negative (%)0.0%0.0%
Memory size247.5 MiB10.6 MiB
2024-11-01T17:08:09.464709image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

 Prior Order Profile ReportTrain Order Profile Report
Minimum14
5-th percentile14
Q156
median1111
Q32421
95-th percentile5452
Maximum99100
Range9896
Interquartile range (IQR)1915

Descriptive statistics

 Prior Order Profile ReportTrain Order Profile Report
Standard deviation17.5350416.614037
Coefficient of variation (CV)1.02292550.97206939
Kurtosis3.2566055.8967139
Mean17.1420517.09141
Median Absolute Deviation (MAD)86
Skewness1.75689632.2433716
Sum5.5599364 × 10823665057
Variance307.47765276.02621
MonotonicityNot monotonicNot monotonic
2024-11-01T17:08:09.643889image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 2078068
 
6.4%
3 2050731
 
6.3%
2 2048332
 
6.3%
4 1820298
 
5.6%
5 1628411
 
5.0%
6 1472238
 
4.5%
7 1333847
 
4.1%
8 1219148
 
3.8%
9 1120468
 
3.5%
10 1028704
 
3.2%
Other values (89) 16634244
51.3%
ValueCountFrequency (%)
4 149882
 
10.8%
5 123548
 
8.9%
6 105328
 
7.6%
7 90949
 
6.6%
8 75645
 
5.5%
9 68366
 
4.9%
10 60216
 
4.3%
11 51530
 
3.7%
12 47819
 
3.5%
13 42072
 
3.0%
Other values (87) 569262
41.1%
ValueCountFrequency (%)
1 2078068
6.4%
2 2048332
6.3%
3 2050731
6.3%
4 1820298
5.6%
5 1628411
5.0%
6 1472238
4.5%
7 1333847
4.1%
8 1219148
3.8%
9 1120468
3.5%
10 1028704
3.2%
ValueCountFrequency (%)
4 149882
10.8%
5 123548
8.9%
6 105328
7.6%
7 90949
6.6%
8 75645
5.5%
9 68366
4.9%
10 60216
4.3%
11 51530
 
3.7%
12 47819
 
3.5%
13 42072
 
3.0%
ValueCountFrequency (%)
4 149882
0.5%
5 123548
0.4%
6 105328
0.3%
7 90949
0.3%
8 75645
0.2%
9 68366
0.2%
10 60216
0.2%
11 51530
 
0.2%
12 47819
 
0.1%
13 42072
 
0.1%
ValueCountFrequency (%)
1 2078068
150.1%
2 2048332
147.9%
3 2050731
148.1%
4 1820298
131.5%
5 1628411
117.6%
6 1472238
106.3%
7 1333847
96.3%
8 1219148
88.0%
9 1120468
80.9%
10 1028704
74.3%

order_dow
Real number (ℝ)

 Prior Order Profile ReportTrain Order Profile Report
Distinct77
Distinct (%)< 0.1%< 0.1%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean2.73881772.7013918
 Prior Order Profile ReportTrain Order Profile Report
Minimum00
Maximum66
Zeros6209666324026
Zeros (%)19.1%23.4%
Negative00
Negative (%)0.0%0.0%
Memory size247.5 MiB10.6 MiB
2024-11-01T17:08:09.764986image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

 Prior Order Profile ReportTrain Order Profile Report
Minimum00
5-th percentile00
Q111
median33
Q355
95-th percentile66
Maximum66
Range66
Interquartile range (IQR)44

Descriptive statistics

 Prior Order Profile ReportTrain Order Profile Report
Standard deviation2.09004912.1676456
Coefficient of variation (CV)0.763120920.80241809
Kurtosis-1.3339893-1.3989458
Mean2.73881772.7013918
Median Absolute Deviation (MAD)22
Skewness0.180192930.1755159
Sum888321523740393
Variance4.36830524.6986876
MonotonicityNot monotonicNot monotonic
2024-11-01T17:08:09.860234image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0 6209666
19.1%
1 5665856
17.5%
6 4500304
13.9%
2 4217798
13.0%
5 4209533
13.0%
3 3844117
11.9%
4 3787215
11.7%
ValueCountFrequency (%)
0 324026
23.4%
6 207279
15.0%
1 205978
14.9%
5 176910
12.8%
2 160562
11.6%
4 155481
11.2%
3 154381
11.1%
ValueCountFrequency (%)
0 6209666
19.1%
1 5665856
17.5%
2 4217798
13.0%
3 3844117
11.9%
4 3787215
11.7%
5 4209533
13.0%
6 4500304
13.9%
ValueCountFrequency (%)
0 324026
23.4%
1 205978
14.9%
2 160562
11.6%
3 154381
11.1%
4 155481
11.2%
5 176910
12.8%
6 207279
15.0%
ValueCountFrequency (%)
0 324026
1.0%
1 205978
0.6%
2 160562
0.5%
3 154381
0.5%
4 155481
0.5%
5 176910
0.5%
6 207279
0.6%
ValueCountFrequency (%)
0 6209666
448.5%
1 5665856
409.2%
2 4217798
304.6%
3 3844117
277.6%
4 3787215
273.5%
5 4209533
304.0%
6 4500304
325.0%

order_hour_of_day
Real number (ℝ)

 Prior Order Profile ReportTrain Order Profile Report
Distinct2424
Distinct (%)< 0.1%< 0.1%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean13.42497713.577592
 Prior Order Profile ReportTrain Order Profile Report
Minimum00
Maximum2323
Zeros2189489083
Zeros (%)0.7%0.7%
Negative00
Negative (%)0.0%0.0%
Memory size247.5 MiB10.6 MiB
2024-11-01T17:08:09.985498image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

 Prior Order Profile ReportTrain Order Profile Report
Minimum00
5-th percentile77
Q11010
median1314
Q31617
95-th percentile2121
Maximum2323
Range2323
Interquartile range (IQR)67

Descriptive statistics

 Prior Order Profile ReportTrain Order Profile Report
Standard deviation4.2463654.238458
Coefficient of variation (CV)0.316303330.31216566
Kurtosis-0.0116575720.043845727
Mean13.42497713.577592
Median Absolute Deviation (MAD)33
Skewness-0.044082776-0.12102981
Sum4.3543228 × 10818799765
Variance18.03161617.964526
MonotonicityNot monotonicNot monotonic
2024-11-01T17:08:10.095545image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
10 2764426
 
8.5%
11 2738582
 
8.4%
14 2691548
 
8.3%
15 2664533
 
8.2%
13 2663292
 
8.2%
12 2620847
 
8.1%
16 2537458
 
7.8%
9 2456713
 
7.6%
17 2089465
 
6.4%
8 1719973
 
5.3%
Other values (14) 7487652
23.1%
ValueCountFrequency (%)
14 119370
 
8.6%
15 116198
 
8.4%
13 114762
 
8.3%
11 114119
 
8.2%
12 111752
 
8.1%
10 110479
 
8.0%
16 110237
 
8.0%
17 96944
 
7.0%
9 93856
 
6.8%
18 76522
 
5.5%
Other values (14) 320378
23.1%
ValueCountFrequency (%)
0 218948
 
0.7%
1 115786
 
0.4%
2 69434
 
0.2%
3 51321
 
0.2%
4 53283
 
0.2%
5 88062
 
0.3%
6 290795
 
0.9%
7 891937
 
2.7%
8 1719973
5.3%
9 2456713
7.6%
ValueCountFrequency (%)
0 9083
 
0.7%
1 5626
 
0.4%
2 3226
 
0.2%
3 2438
 
0.2%
4 2431
 
0.2%
5 3847
 
0.3%
6 11847
 
0.9%
7 36302
 
2.6%
8 67386
4.9%
9 93856
6.8%
ValueCountFrequency (%)
0 9083
 
< 0.1%
1 5626
 
< 0.1%
2 3226
 
< 0.1%
3 2438
 
< 0.1%
4 2431
 
< 0.1%
5 3847
 
< 0.1%
6 11847
 
< 0.1%
7 36302
 
0.1%
8 67386
0.2%
9 93856
0.3%
ValueCountFrequency (%)
0 218948
 
15.8%
1 115786
 
8.4%
2 69434
 
5.0%
3 51321
 
3.7%
4 53283
 
3.8%
5 88062
 
6.4%
6 290795
 
21.0%
7 891937
 
64.4%
8 1719973
124.2%
9 2456713
177.4%

days_since_prior_order
Real number (ℝ)

 Prior Order Profile ReportTrain Order Profile Report
Distinct3131
Distinct (%)< 0.1%< 0.1%
Missing20780680
Missing (%)6.4%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean11.10407417.066126
 Prior Order Profile ReportTrain Order Profile Report
Minimum00
Maximum3030
Zeros44869817044
Zeros (%)1.4%1.2%
Negative00
Negative (%)0.0%0.0%
Memory size247.5 MiB10.6 MiB
2024-11-01T17:08:10.221528image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

 Prior Order Profile ReportTrain Order Profile Report
Minimum00
5-th percentile23
Q157
median815
Q31530
95-th percentile3030
Maximum3030
Range3030
Interquartile range (IQR)1023

Descriptive statistics

 Prior Order Profile ReportTrain Order Profile Report
Standard deviation8.778914310.426418
Coefficient of variation (CV)0.790602990.61094228
Kurtosis-0.068967377-1.5712889
Mean11.10407417.066126
Median Absolute Deviation (MAD)49
Skewness1.05397220.074891246
Sum3.3707995 × 10823630048
Variance77.069337108.71019
MonotonicityNot monotonicNot monotonic
2024-11-01T17:08:10.368660image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
7 3479504
 
10.7%
30 3070057
 
9.5%
6 2519939
 
7.8%
5 2126420
 
6.6%
4 2080560
 
6.4%
8 1933815
 
6.0%
3 1877881
 
5.8%
2 1464875
 
4.5%
9 1218973
 
3.8%
14 1030605
 
3.2%
Other values (21) 9553792
29.5%
(Missing) 2078068
 
6.4%
ValueCountFrequency (%)
30 407265
29.4%
7 106801
 
7.7%
6 72138
 
5.2%
8 61821
 
4.5%
5 54117
 
3.9%
14 51690
 
3.7%
4 45727
 
3.3%
9 43410
 
3.1%
13 39081
 
2.8%
3 36550
 
2.6%
Other values (21) 466017
33.7%
ValueCountFrequency (%)
0 448698
 
1.4%
1 941116
 
2.9%
2 1464875
4.5%
3 1877881
5.8%
4 2080560
6.4%
5 2126420
6.6%
6 2519939
7.8%
7 3479504
10.7%
8 1933815
6.0%
9 1218973
 
3.8%
ValueCountFrequency (%)
0 17044
 
1.2%
1 19265
 
1.4%
2 27504
 
2.0%
3 36550
 
2.6%
4 45727
3.3%
5 54117
3.9%
6 72138
5.2%
7 106801
7.7%
8 61821
4.5%
9 43410
3.1%
ValueCountFrequency (%)
0 17044
 
0.1%
1 19265
 
0.1%
2 27504
 
0.1%
3 36550
 
0.1%
4 45727
0.1%
5 54117
0.2%
6 72138
0.2%
7 106801
0.3%
8 61821
0.2%
9 43410
0.1%
ValueCountFrequency (%)
0 448698
 
32.4%
1 941116
 
68.0%
2 1464875
105.8%
3 1877881
135.6%
4 2080560
150.3%
5 2126420
153.6%
6 2519939
182.0%
7 3479504
251.3%
8 1933815
139.7%
9 1218973
 
88.0%

Interactions

Prior Order Profile Report

2024-11-01T17:05:49.987464image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Train Order Profile Report

2024-11-01T17:07:59.334620image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Prior Order Profile Report

2024-11-01T17:02:37.887980image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Train Order Profile Report

2024-11-01T17:07:45.883952image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Prior Order Profile Report

2024-11-01T17:03:04.936382image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Train Order Profile Report

2024-11-01T17:07:47.753426image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Prior Order Profile Report

2024-11-01T17:03:32.869215image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Train Order Profile Report

2024-11-01T17:07:49.684567image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Prior Order Profile Report

2024-11-01T17:03:59.968371image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Train Order Profile Report

2024-11-01T17:07:51.685041image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Prior Order Profile Report

2024-11-01T17:04:27.119539image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Train Order Profile Report

2024-11-01T17:07:53.767938image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Prior Order Profile Report

2024-11-01T17:04:53.522860image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Train Order Profile Report

2024-11-01T17:07:55.620187image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Prior Order Profile Report

2024-11-01T17:05:20.718091image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Train Order Profile Report

2024-11-01T17:07:57.521219image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Prior Order Profile Report

2024-11-01T17:05:54.070040image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Train Order Profile Report

2024-11-01T17:07:59.584727image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Prior Order Profile Report

2024-11-01T17:02:41.271560image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Train Order Profile Report

2024-11-01T17:07:46.118028image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Prior Order Profile Report

2024-11-01T17:03:08.468747image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Train Order Profile Report

2024-11-01T17:07:47.984640image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Prior Order Profile Report

2024-11-01T17:03:36.236341image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Train Order Profile Report

2024-11-01T17:07:49.917969image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Prior Order Profile Report

2024-11-01T17:04:03.338308image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Train Order Profile Report

2024-11-01T17:07:51.918025image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Prior Order Profile Report

2024-11-01T17:04:30.474188image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Train Order Profile Report

2024-11-01T17:07:54.016725image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Prior Order Profile Report

2024-11-01T17:04:56.818204image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Train Order Profile Report

2024-11-01T17:07:55.867831image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Prior Order Profile Report

2024-11-01T17:05:24.451676image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Train Order Profile Report

2024-11-01T17:07:57.734658image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Prior Order Profile Report

2024-11-01T17:05:58.220925image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Train Order Profile Report

2024-11-01T17:07:59.834447image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Prior Order Profile Report

2024-11-01T17:02:44.604698image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Train Order Profile Report

2024-11-01T17:07:46.351350image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Prior Order Profile Report

2024-11-01T17:03:11.952339image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Train Order Profile Report

2024-11-01T17:07:48.234931image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Prior Order Profile Report

2024-11-01T17:03:39.472200image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Train Order Profile Report

2024-11-01T17:07:50.167934image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Prior Order Profile Report

2024-11-01T17:04:06.635708image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Train Order Profile Report

2024-11-01T17:07:52.300989image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Prior Order Profile Report

2024-11-01T17:04:33.803143image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Train Order Profile Report

2024-11-01T17:07:54.251491image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Prior Order Profile Report

2024-11-01T17:05:00.086202image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Train Order Profile Report

2024-11-01T17:07:56.084545image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Prior Order Profile Report

2024-11-01T17:05:27.873030image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Train Order Profile Report

2024-11-01T17:07:57.984523image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Prior Order Profile Report

2024-11-01T17:06:02.237070image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Train Order Profile Report

2024-11-01T17:08:00.084618image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Prior Order Profile Report

2024-11-01T17:02:47.907641image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Train Order Profile Report

2024-11-01T17:07:46.588061image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Prior Order Profile Report

2024-11-01T17:03:15.419078image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Train Order Profile Report

2024-11-01T17:07:48.468012image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Prior Order Profile Report

2024-11-01T17:03:42.806352image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Train Order Profile Report

2024-11-01T17:07:50.401129image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Prior Order Profile Report

2024-11-01T17:04:10.369088image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Train Order Profile Report

2024-11-01T17:07:52.567774image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Prior Order Profile Report

2024-11-01T17:04:37.140425image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Train Order Profile Report

2024-11-01T17:07:54.484941image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Prior Order Profile Report

2024-11-01T17:05:03.333919image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Train Order Profile Report

2024-11-01T17:07:56.334764image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Prior Order Profile Report

2024-11-01T17:05:31.533732image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Train Order Profile Report

2024-11-01T17:07:58.222692image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Prior Order Profile Report

2024-11-01T17:06:06.588041image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Train Order Profile Report

2024-11-01T17:08:00.320206image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Prior Order Profile Report

2024-11-01T17:02:51.169461image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Train Order Profile Report

2024-11-01T17:07:46.817960image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Prior Order Profile Report

2024-11-01T17:03:18.920554image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Train Order Profile Report

2024-11-01T17:07:48.706527image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Prior Order Profile Report

2024-11-01T17:03:46.236115image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Train Order Profile Report

2024-11-01T17:07:50.651458image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Prior Order Profile Report

2024-11-01T17:04:13.669440image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Train Order Profile Report

2024-11-01T17:07:52.817847image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Prior Order Profile Report

2024-11-01T17:04:40.286708image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Train Order Profile Report

2024-11-01T17:07:54.684612image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Prior Order Profile Report

2024-11-01T17:05:06.568363image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Train Order Profile Report

2024-11-01T17:07:56.568211image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Prior Order Profile Report

2024-11-01T17:05:35.071642image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Train Order Profile Report

2024-11-01T17:07:58.434628image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Prior Order Profile Report

2024-11-01T17:06:10.554041image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Train Order Profile Report

2024-11-01T17:08:00.567945image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Prior Order Profile Report

2024-11-01T17:02:54.590353image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Train Order Profile Report

2024-11-01T17:07:47.051104image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Prior Order Profile Report

2024-11-01T17:03:22.385459image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Train Order Profile Report

2024-11-01T17:07:48.934685image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Prior Order Profile Report

2024-11-01T17:03:49.635108image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Train Order Profile Report

2024-11-01T17:07:50.867978image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Prior Order Profile Report

2024-11-01T17:04:16.958490image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Train Order Profile Report

2024-11-01T17:07:53.069775image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Prior Order Profile Report

2024-11-01T17:04:43.548963image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Train Order Profile Report

2024-11-01T17:07:54.918096image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Prior Order Profile Report

2024-11-01T17:05:09.770288image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Train Order Profile Report

2024-11-01T17:07:56.784944image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Prior Order Profile Report

2024-11-01T17:05:38.703968image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Train Order Profile Report

2024-11-01T17:07:58.651464image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Prior Order Profile Report

2024-11-01T17:06:14.039645image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Train Order Profile Report

2024-11-01T17:08:00.834323image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Prior Order Profile Report

2024-11-01T17:02:57.836370image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Train Order Profile Report

2024-11-01T17:07:47.284823image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Prior Order Profile Report

2024-11-01T17:03:25.919094image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Train Order Profile Report

2024-11-01T17:07:49.184077image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Prior Order Profile Report

2024-11-01T17:03:53.069198image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Train Order Profile Report

2024-11-01T17:07:51.118034image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Prior Order Profile Report

2024-11-01T17:04:20.252637image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Train Order Profile Report

2024-11-01T17:07:53.301303image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Prior Order Profile Report

2024-11-01T17:04:46.787241image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Train Order Profile Report

2024-11-01T17:07:55.167283image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Prior Order Profile Report

2024-11-01T17:05:13.437996image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Train Order Profile Report

2024-11-01T17:07:57.003871image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Prior Order Profile Report

2024-11-01T17:05:42.341194image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Train Order Profile Report

2024-11-01T17:07:58.884632image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Prior Order Profile Report

2024-11-01T17:06:17.253915image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Train Order Profile Report

2024-11-01T17:08:01.067112image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Prior Order Profile Report

2024-11-01T17:03:01.406583image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Train Order Profile Report

2024-11-01T17:07:47.504265image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Prior Order Profile Report

2024-11-01T17:03:29.519342image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Train Order Profile Report

2024-11-01T17:07:49.433895image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Prior Order Profile Report

2024-11-01T17:03:56.569957image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Train Order Profile Report

2024-11-01T17:07:51.351257image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Prior Order Profile Report

2024-11-01T17:04:23.769147image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Train Order Profile Report

2024-11-01T17:07:53.534686image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Prior Order Profile Report

2024-11-01T17:04:50.219233image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Train Order Profile Report

2024-11-01T17:07:55.384824image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Prior Order Profile Report

2024-11-01T17:05:17.038270image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Train Order Profile Report

2024-11-01T17:07:57.284405image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Prior Order Profile Report

2024-11-01T17:05:46.105885image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Train Order Profile Report

2024-11-01T17:07:59.118077image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Correlations

Prior Order Profile Report

2024-11-01T17:08:10.549522image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Train Order Profile Report

2024-11-01T17:08:10.691800image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Prior Order Profile Report

add_to_cart_orderdays_since_prior_orderorder_doworder_hour_of_dayorder_idorder_numberproduct_idreordereduser_id
add_to_cart_order1.0000.078-0.015-0.015-0.0000.0000.0090.0960.000
days_since_prior_order0.0781.000-0.043-0.004-0.000-0.3850.0010.1400.000
order_dow-0.015-0.0431.0000.0120.0010.015-0.0030.018-0.002
order_hour_of_day-0.015-0.0040.0121.0000.001-0.0480.0010.0380.000
order_id-0.000-0.0000.0010.0011.000-0.000-0.0000.001-0.000
order_number0.000-0.3850.015-0.048-0.0001.000-0.0020.341-0.001
product_id0.0090.001-0.0030.001-0.000-0.0021.0000.0400.000
reordered0.0960.1400.0180.0380.0010.3410.0401.0000.004
user_id0.0000.000-0.0020.000-0.000-0.0010.0000.0041.000

Train Order Profile Report

add_to_cart_orderdays_since_prior_orderorder_doworder_hour_of_dayorder_idorder_numberproduct_idreordereduser_id
add_to_cart_order1.0000.018-0.024-0.0100.0020.0310.0070.137-0.000
days_since_prior_order0.0181.000-0.0250.0080.003-0.3870.0010.1660.004
order_dow-0.024-0.0251.0000.0090.0010.015-0.0040.017-0.006
order_hour_of_day-0.0100.0080.0091.000-0.003-0.0350.0020.034-0.001
order_id0.0020.0030.001-0.0031.0000.002-0.0010.004-0.001
order_number0.031-0.3870.015-0.0350.0021.000-0.0010.237-0.005
product_id0.0070.001-0.0040.002-0.001-0.0011.0000.042-0.001
reordered0.1370.1660.0170.0340.0040.2370.0421.0000.006
user_id-0.0000.004-0.006-0.001-0.001-0.005-0.0010.0061.000

Missing values

Prior Order Profile Report

2024-11-01T17:06:18.553543image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
A simple visualization of nullity by column.

Train Order Profile Report

2024-11-01T17:08:01.332405image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
A simple visualization of nullity by column.

Prior Order Profile Report

2024-11-01T17:06:32.419362image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Train Order Profile Report

2024-11-01T17:08:01.851039image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

Prior Order Profile Report

order_idproduct_idadd_to_cart_orderreordereduser_ideval_setorder_numberorder_doworder_hour_of_daydays_since_prior_order
023312011202279prior3598.0
122898521202279prior3598.0
22932730202279prior3598.0
324591841202279prior3598.0
423003550202279prior3598.0
521779461202279prior3598.0
624014171202279prior3598.0
72181981202279prior3598.0
824366890202279prior3598.0
933375411205970prior1651712.0

Train Order Profile Report

order_idproduct_idadd_to_cart_orderreordereduser_ideval_setorder_numberorder_doworder_hour_of_daydays_since_prior_order
014930211112108train44109.0
111110921112108train44109.0
211024630112108train44109.0
314968340112108train44109.0
414363351112108train44109.0
511317660112108train44109.0
614720970112108train44109.0
712203581112108train44109.0
836396121079431train2361830.0
936196602179431train2361830.0

Prior Order Profile Report

order_idproduct_idadd_to_cart_orderreordereduser_ideval_setorder_numberorder_doworder_hour_of_daydays_since_prior_order
32434479342108378541025247prior242621.0
324344803421083453092025247prior242621.0
324344813421083211623025247prior242621.0
324344823421083181764125247prior242621.0
324344833421083352115025247prior242621.0
324344843421083396786125247prior242621.0
324344853421083113527025247prior242621.0
32434486342108346008025247prior242621.0
324344873421083248529125247prior242621.0
324344883421083502010125247prior242621.0

Train Order Profile Report

order_idproduct_idadd_to_cart_orderreordereduser_ideval_setorder_numberorder_doworder_hour_of_daydays_since_prior_order
138460734210583031661136952train2031815.0
138460834210583557870136952train2031815.0
138460934210583265081136952train2031815.0
138461034210634923511169679train300104.0
138461134210631356521169679train300104.0
138461234210631423331169679train300104.0
138461334210633554841169679train300104.0
138461434210703595111139822train156108.0
138461534210701695321139822train156108.0
13846163421070472431139822train156108.0

Duplicate rows

Prior Order Profile Report

order_idproduct_idadd_to_cart_orderreordereduser_ideval_setorder_numberorder_doworder_hour_of_daydays_since_prior_order# duplicates
Dataset does not contain duplicate rows.

Train Order Profile Report

order_idproduct_idadd_to_cart_orderreordereduser_ideval_setorder_numberorder_doworder_hour_of_daydays_since_prior_order# duplicates
Dataset does not contain duplicate rows.